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TED Talks Daily

How to make AI a force for good in climate | Amen Ra Mashariki and Manoush Zomorodi

TED Talks Daily

TED

Ted Podcast, Ted, Ted Talks, Society & Culture, Ted Talks Daily

4.1 β€’ 11.9K Ratings

πŸ—“οΈ 19 December 2025

⏱️ 13 minutes

🧾️ Download transcript

Summary

In a now-famous Go match against a human in 2016, AI made Move 37 β€” a seemingly nonsensical play that baffled every expert but ultimately won it the match. Amen Ra Mashariki, director of AI at the Bezos Earth Fund, thinks we need AI to make that same kind of creative leap for climate solutions. In conversation with TED Radio Hour host Manoush Zomorodi, he shares a vision for new AI solutions to environmental problems that human experts haven't yet dreamed up.



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Transcript

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0:00.0

You're listening to TED Talks Daily, where we bring you new ideas to spark your curiosity every day.

0:11.9

I'm your host, Elise Hugh.

0:13.6

I'm still amazed by the ridiculously fast pace at which technology and AI is growing.

0:20.0

But what are some ways that AI might be used for climate and nature solutions?

0:25.0

Today, Manus Zomerooti, who hosts the TED Radio Hour, sits down with AI changemaker

0:30.1

Amen Ra Masa Rishi to discuss what he thinks truly game-changing climate ideas might look like and how AI is playing

0:39.6

an increasingly large role in that space.

0:46.3

Okay, so tell us the story of how you got to be working with Bezos, your sort of trajectory to being here.

0:55.3

Yeah, it's really interesting that you ask that question

0:57.3

because sort of my pathway to the Bezos Earth Fund

1:00.6

is almost polar opposite to how we think about our pathway

1:05.9

to adopting and using AI to accelerate climate and nature solutions.

1:15.6

And I'll explain why really, really, and some quick points. I, undergrad, master's, doctorate computer science.

1:19.6

Computer scientists, research labs did the whole thing.

1:22.6

I was one of those computer scientists that believed in computer science,

1:25.6

you know, algorithm optimization.

1:29.2

Through a couple of personal things that took place, I realized that that was only a mechanism

1:35.6

by which I could do other things, which is have an impact.

1:38.5

So then I began to chase problems.

1:41.4

You mentioned here, I was the chief analytics officer for the city of New York.

1:45.3

How do we solve problems here? And then, you know, coming to the Basel Earth Fund, how do we

1:51.7

use AI computer science to solve climate and nature problems? And so I was AI in search of a problem

...

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